The present embodiments relate to magnetic resonance imaging (MRI). In particular, parallel imaging is provided.
Parallel imaging provides for fast image acquisition for MRI. Parallel imaging includes image domain approaches (e.g., SENSE) and k-space reconstruction approaches (e.g., GRAPPA). These approaches are essentially linear in the sense that unknowns (e.g., MR images or k-space points) are solved as the solution to a least-square problem (AX=b). An advantage for the linear formulation is the relatively low computational cost.
Parallel imaging may speedup the acquisition time by acquiring a less dense sampling. The speedup or field-of-view reduction factor practical for a state-of-art clinical phased array coil is limited for most applications. There is a tradeoff between signal-noise-ratio (SNR) and artifacts for linear parallel imaging. Further increase of the reduction factor (R) along the phase encoding direction results in greater artifacts.
Parallel imaging may be formulated as a nonlinear problem. Iterative Self-consistent Parallel Imaging Reconstruction (SPIRiT) is a nonlinear parallel imaging technique. In this framework, every k-space point is estimated from all surrounding points including acquired and not acquired ones. As a result, the not acquired points cannot be directly solved as a least-square solution. With proper regularization, a better trade-off between SNR and artifacts may be feasible. However, these benefits may be reduced for dynamic or real-time imaging.